Leadership Commitment for RAI

Summary: Achieving leadership commitment to RAI within an organization requires the management team to actively invest their time and effort into building RAI practices within an organization.

Type of pattern: Governance pattern

Type of objective: Trustworthiness

Target users: Management teams

Impacted stakeholders: Employees, AI users, AI impacted subjects, AI consumers

Lifecycle stages: All stages

Relevant AI ethics principles: Human, societal and environmental wellbeing, human-centered values, fairness, privacy protection and security, reliability and safety, transparency and explainability, contestability, accountability

Mapping to AI regulations/standards: EU AI Act, ISO/IEC 42001:2023 Standard.

Context: AI has the potential to transform organizations through a wide range of applications, such as analyzing business data or optimizing hiring processes. However, successful AI adoption relies heavily on the management team’s commitment to building responsible AI within an organization.

Problem: How can the management team ensure commitment to build RAI within an organization?

Solution: Leadership commitment is crucial for effective organization-level governance of RAI. Management teams can demonstrate their commitment to RAI within an organization in several ways. For example, the management team can establish clear founding ethics principles and governance structure for the organization [1]. They can also make RAI a key part of CEO contracts and performance reviews, appoint an executive responsible for RAI, set up an organization-level risk committee, promote a culture of RAI within the organization, and provide training and guidelines on RAI practices to employees.


  • Formation of a culture: Continuous leadership commitment is the foundation of a strong organizational culture that values and promotes RAI.
  • Realization of vision: Strong leadership commitment to RAI can help ensure that an organization’s vision for AI is realized.
  • Visible sponsorship: By visible supporting and promoting RAI, leadership commitment can build the organization’s capacity for RAI practices.


  • Additional efforts: Establishing and maintaining leadership commitment to RAI can require significant time and efforts.
  • Extra cost: Implementing leadership commitment may require additional financial and resource costs.

Related patterns:

  • RAI risk committee: An RAI risk committee is an important component of the RAI governance structure that is established through leadership commitment.
  • Code for RAI: The management team enforces the code of ethics within an organization.

Known uses:

  • IBM has established an AI ethics board to support a culture of responsible AI throughout IBM.
  • Axon has assembled an independent AI ethics board to provide guidance on the development of its AI products and services.
  • Schneider Electric has appointed its first Chief AI Officer to advance its AI strategy.


[1] Shneiderman, B., Bridging the gap between ethics and practice: Guidelines for reliable, safe, and trustworthy Human-Centered AI systems. ACM Transactions on Interactive Intelligent Systems (TiiS), 2020. 10(4): p. 1-31.